python - Pandas 选择多个日期时间之间的数据框行

Question

当前 df:

Date                 Power
2011-04-18 17:00:00  243.56
2011-04-18 17:00:01  245.83
2011-04-18 17:00:02  246.02
2011-04-18 17:00:03  245.72
2011-04-18 17:00:04  244.71
2011-04-18 17:00:05  245.93
2011-04-18 17:00:06  243.12
2011-04-18 17:00:07  244.72
2011-04-18 17:00:08  242.44
2011-04-18 17:00:09  246.42
2011-04-18 17:00:10  245.02
...                     ...

我有带日期和 float 的 df。日期是索引并且是唯一的。我想根据在下一个 df 中找到的日期创建一个新的 df。

     date start          date end
0    2011-04-18 17:00:01 2011-04-18 17:00:02
1    2011-04-18 17:00:05 2011-04-18 17:00:06
2    2011-04-18 17:00:08 2011-04-18 17:00:10
...                  ...                 ...

我希望得到:

Date                 Power
2011-04-18 17:00:01  245.83
2011-04-18 17:00:02  246.02
2011-04-18 17:00:05  245.93
2011-04-18 17:00:06  243.12
2011-04-18 17:00:08  242.44
2011-04-18 17:00:09  246.42
2011-04-18 17:00:10  245.02
...                     ...

换句话说，我想过滤初始 df 并找到第二个 df 中找到的所有日期之间的所有行。

我想到了使用 pandas.DataFrame.between_time。但问题是这仅适用于 1 个给定的开始日期和结束日期。如何在多个不同的日期期间执行此操作？

Answer 1

使用np.logical_or.reduce列表理解:

L = [df1['Date'].between(s, e) for s, e in df2[['date start','date end']].to_numpy()]

df = df1[np.logical_or.reduce(L)]
print (df)
                  Date   Power
1  2011-04-18 17:00:01  245.83
2  2011-04-18 17:00:02  246.02
5  2011-04-18 17:00:05  245.93
6  2011-04-18 17:00:06  243.12
8  2011-04-18 17:00:08  242.44
9  2011-04-18 17:00:09  246.42
10 2011-04-18 17:00:10  245.02

如果可以使用 DatetimeIndex:

L = [df1[s:e] for s, e in df2[['date start','date end']].to_numpy()]

df = pd.concat(L)
print (df)
                      Power
Date                       
2011-04-18 17:00:01  245.83
2011-04-18 17:00:02  246.02
2011-04-18 17:00:05  245.93
2011-04-18 17:00:06  243.12
2011-04-18 17:00:08  242.44
2011-04-18 17:00:09  246.42
2011-04-18 17:00:10  245.02



L = [(df1.index >= s) & (df1.index <= e) 
     for s, e in df2[['date start','date end']].to_numpy()]

df = df1[np.logical_or.reduce(L)]